Inference in Mixed Proportional Hazard Models with K Random Effects

A general formulation of Mixed Proportional Hazard models with K random effects is provided. It enables to account for a population stratified at K different levels. We then show how to approximate the partial maximum likelihood estimator using an EM algorithm. In a Monte Carlo study, the behavior of the estimator is assessed and I provide an application to the ratification of ILO conventions. Compared to other procedures, the results indicate an important decrease in computing time, as well as improved convergence and stability

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Year of publication:	2010
Authors:	Horny, Guillaume
Publisher:	[S.l.] : SSRN
Subject:	Statistische Bestandsanalyse \| Duration analysis \| Theorie \| Theory \| Mehrebenenanalyse \| Multi-level analysis \| Maximum-Likelihood-Schätzung \| Maximum likelihood estimation \| Monte-Carlo-Simulation \| Monte Carlo simulation \| Algorithmus \| Algorithm